title: Functional architecture of Escherichia coli: new insights provided by a natural decomposition approach.
abstract: BACKGROUND
  Previous studies have used different methods in an effort to extract the modular organization of transcriptional regulatory networks. However, these approaches are not natural, as they try to cluster strongly connected genes into a module or locate known pleiotropic transcription factors in lower hierarchical layers. Here, we unravel the transcriptional regulatory network of Escherichia coli by separating it into its key elements, thus revealing its natural organization. We also present a mathematical criterion, based on the topological features of the transcriptional regulatory network, to classify the network elements into one of two possible classes: hierarchical or modular genes.
  
  
  RESULTS
  We found that modular genes are clustered into physiologically correlated groups validated by a statistical analysis of the enrichment of the functional classes. Hierarchical genes encode transcription factors responsible for coordinating module responses based on general interest signals. Hierarchical elements correlate highly with the previously studied global regulators, suggesting that this could be the first mathematical method to identify global regulators. We identified a new element in transcriptional regulatory networks never described before: intermodular genes. These are structural genes that integrate, at the promoter level, signals coming from different modules, and therefore from different physiological responses. Using the concept of pleiotropy, we have reconstructed the hierarchy of the network and discuss the role of feedforward motifs in shaping the hierarchical backbone of the transcriptional regulatory network.
  
  
  CONCLUSIONS
  This study sheds new light on the design principles underpinning the organization of transcriptional regulatory networks, showing a novel nonpyramidal architecture composed of independent modules globally governed by hierarchical transcription factors, whose responses are integrated by intermodular genes.
authors.affiliation: Programa de Genómica Computacional, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Avenida Universidad s/n, Col. Chamilpa, Cuernavaca, Morelos, México. jfreyre@ccg.unam.mx
authors.forename: Julio A
authors.initials: JA
authors.lastname: Freyre-González
authors.forename: José A
authors.initials: JA
authors.lastname: Alonso-Pavón
authors.forename: Luis G
authors.initials: LG
authors.lastname: Treviño-Quintanilla
authors.forename: Julio
authors.initials: J
authors.lastname: Collado-Vides
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D004926:Escherichia coli / Q000235:genetics*; D029968:Escherichia coli Proteins / Q000235:genetics*; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks / Q000235:genetics*; D005798:Genes, Bacterial; D016680:Genome, Bacterial
chemical_list: D029968:Escherichia coli Proteins